Estimation of WHAM7 constants for GaIII, InIII, SbIII and BiIII from linear free energy relationships, and speciation calculations for natural waters

Abstract

Environmental contextNatural organic matter exerts a powerful control on chemical conditions in waters and soils, affecting pH and influencing the biological availability, transport and retention of metals. Modelling can help to predict these effects, but for many metals, model parameters are missing. We report parameters for four technology-critical elements in a chemical speciation model, and consider the chemistries of the elements in natural waters. AbstractWe compiled the equilibrium constants for the interactions of the technology-critical elements (TCEs) GaIII, InIII, SbIII and BiIII with ammonia, fluoride, hydroxyl and ligands with oxygen atoms. We then combined them with predictive equations to estimate parameters for Humic Ion-Binding Model VII, which permits the calculation of metal binding by natural organic matter (fulvic acid, FA, and humic acid, HA). Derived values of the Model VII parameter quantifying the interaction of metal ions with carboxyl-type groups (log KMA) were among the highest estimated so far, as were the values for the parameter (ΔLK2) that quantifies the tendency of the metal ion to interact with softer ligand atoms (N and S). The Windermere Humic Aqueous Model, version 7 (WHAM7), which incorporates Model VII, was then used to estimate the chemical speciation of each TCE element.

Molecular Probing of DOM Indicates a Key Role of Spruce-Derived Lignin in the DOM and Metal Cycles of a Headwater Catchment: Can Spruce Forest Dieback Exacerbate Future Trends in the Browning of Central European Surface Waters?

“…We recognize, though, that the role of peatland DOM would probably be stronger if more high-discharge samples from the peat outlets had been obtained or if streams draining large degraded or restored peatlands were included. It has often been argued that the DOM in forested areas of boreal and temperate forests in Europe is dependent on flows of organic-rich riparian wetlands “lining” headwater streams. ,− , Indeed, the floodplains in the study area include such wet sections, dominated by sedges and grasses. The DOM composition data make it very unlikely that it originates from these zones, as P / F would be higher in case of significant graminoid contributions.…”

“…The PCA also highlights two factors underlying the variations in metal concentrations. Both PC1 ICP (50% of the total variance) and PC2 ICP (17%) are related to DOM-binding affinity, that is, negative loadings on PC1 ICP for the AEM which are mobile elements with no or low affinity (limited to electrostatic interactions). , The other metals have positive loadings on PC1 ICP and are separated into two groups along PC2 ICP (Figure a): Fe, As, Cr, Cu, and Ti with high DOM affinity (positive loadings) and Al, Cd, La, Mn, Ni, and Zn with moderate affinity (negative loadings). − The PC1 ICP scores are correlated with DOC for the whole sample set and for individual seasons (Figure a and Table ), whereas the PC2 ICP scores are correlated to DOC only during spring and autumn (Table ). The metals with negative loadings on PC2 ICP (Al, Cd, La, Mn, Ni, and Zn) are decoupled from the DOM cycle during spring and autumn, probably because of the combination of their weak capacity to compete with, in particular, Fe for DOM binding sites, limited capacity to form multidentate, chelate-type complexes, and their weak affinity for colloids of Fe–DOM complexes (ternary binding) (Section ).…”

“…The metals with negative loadings on PC2 ICP (Al, Cd, La, Mn, Ni, and Zn) are decoupled from the DOM cycle during spring and autumn, probably because of the combination of their weak capacity to compete with, in particular, Fe for DOM binding sites, limited capacity to form multidentate, chelate-type complexes, and their weak affinity for colloids of Fe–DOM complexes (ternary binding) (Section ). Commonly used models of DOM–metal interactions employ intrinsic equilibrium constants of two metal-binding site types ( K ma and K mb ) and a parameter of binding heterogeneity (Δ LK 2 ). , Based on the data of 13 metals extracted from the study of Tipping et al, , K ma is correlated to loadings on PC1 ICP , Δ LK 2 to PC2 ICP , and a combined parameter of PC1 ICP and PC2 ICP explains 93% of the variation of the combined parameter of K ma and Δ LK 2 (Figure S1). Conforming the common interpretation of these parameters, PC1 ICP reflects weak (monodentate) interactions with the carboxylic moieties of DOM, whereas PC2 ICP would reflect stronger (bi- or tridentate) ones.…”

Bismuth(III) Forms Exceptionally Strong Complexes with Natural Organic Matter

“… a The carboxylate group density of the FA was 11.16 mequiv. (g C) −1 b Based on the carbon content given by IHSS …”

“…Geochemical models, such as WHAM-Model VII, NICA-Donnan, and SHM, are useful tools to evaluate metal binding experiments involving natural organic matter and to predict the geochemical behavior of metals in soils and waters. For many metals, extensive data sets for isolated humic and fulvic acids (FAs) are available for calibration of these models. − However, as recently noted by Tipping and Filella, no such data are available for bismuth­(III). Instead, these authors used linear free-energy relationships with hydroxide and fluoride ions to parameterize the WHAM-Model VII for bismuth­(III).…”